Synopsis

Using some remarkable tools to illustrate the case, consultant and researcher Bill Brockbank examines and
quantifies the impacts of inertia & momentum in the supply chain before drawing some general conclusions.

Inertia and Momentum in Supply Chains

Introduction

The notion that supply chains have 'inertia' is perhaps half understood. That is to say, it's well
accepted that when sales are high it takes time for the supply chain to catch up. However, there's
another side to this coin, that when sales slow down the supply chain 'keeps coming'. In the short
term this overfills store shelves, robbing the store of space it could perhaps use to sell something
else. In the medium term it leads to warehouses with unwanted product yet out-of-stock of crucial
(other) products. In the long term, say a season, it leads to stock markdowns and write-offs.

For this paper we have used a retail supply
chain, although the lessons apply to all ex stock
chains. Retail, characterised by low
rates of sale (per SKU, per store) and the
universal need to 'push' some stock in
anticipation of sales is the clearest illustration
of inertia. It's also the area with the biggest
profit potential, much of it unrecognised.
To distinguish between 'speed up' and 'slow
down' inertia, we'll call the latter
momentum.

We'll examine the micro chain, between the
store and its local Distribution Centre (DC).
The lessons are the same for the supplier >>
DC echelon, for the manufacturer >>
importer, for the manufacturer's supplier to
the factory and so on.

In one sense the
momentum at these upper echelons is greater
because the lead time is longer. On the other
hand, the impact of momentum is less clearcut.
That's because the sole purpose of a retail
chain is to have something in each shop.
Everything else is, broadly, a step along the
way. We shouldn't care about out-of-stock in
the DC providing we lose no shop sales. Yet
too many firms measure line fill (the converse
of out-of-stock) in the DC because they can;
for all sorts of reasons they don't measure
out-of-stock in the stores, or they report
something easy to measure which purports to
represent OOS[1]

Our retail store also has 'a place for
everything and everything in its place'. Corn
Flakes can't overflow into the Rice Krispies
shelf space or vice versa. Typically, mid
priced goods with fixed shelf allocations work
like this, while hanging goods do not.
In essence the micro chain contains:-

A number of retail outlets each with a target
stock for each ranged SKU. We'll examine
only one shop[2], from which the lessons are
scaleable.

A DC (or factory, or agent, or importer or
wholesaler) who supply, on demand, SKU's
to replenish the shop.

A control mechanism with 'triggers' and
'rules' to make this happen.

A leading high street chain thought its store out-of-stock
was 11% when the customers saw 28%. The
differences? Inaccurate store stock records; and
counting backroom and in transit stock as 'on display'.

It's a pretty busy shop! We ran over 2,000
combinations of BTL, rate of sale and lead time, each
10,000 times. Our 'one store' not only worked
extremely hard, it experienced every possible
combination of circumstances.